To improve the classification accuracy, some works are considered to jointly exploit the spectral and spatial information contained in HSI. For instance, [1]} introduced a DBN framework with the logistics regression layer and verified that the joint exploitation of spectral-spatial features leads to improved classification accuracy. Similarly, [2]} proposed a spectral-spatial graph-based RBM method for HSIC which constructs the spectral-spatial graph through joint similarity measurement based on spectral and spatial details, then an RBM is trained to extract useful joint spectral-spatial features from HSI, and finally, these features are passed to a DBN and logistic regression layer for classification.
